Reinforcement Learning papers, 2023–2026

Key findings

• Reinforcement Learning went from 1,070 papers in 2023 to 2,985 in 2026, roughly 2.8x in three years.
• NeurIPS publishes the most Reinforcement Learning work: 2,494 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Reasoning Models: papers tagged with both rose from 9 in 2023 to 437 in 2026.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
• ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
• ICLR 2026$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space
• CVPR 2026A Causal Marriage between VLM and IRM from Understanding to
• NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
• ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
• ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
• CVPR 2025All-Optical Nonlinear Diffractive Deep Network for Ultrafast Image Denoising
• NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
• ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
• ICLR 2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
• CVPR 2024DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning
• NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
• ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
• ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
• CVPR 2023"Seeing" Electric Network Frequency From Events
• NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
• ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
• ICLR 2026$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning
• CVPR 2026AdaptVision Efficient Vision-Language Models via Adaptive Visual Acquisition

All Reinforcement Learning papers

379 papers, page 5 of 8

201. ICLR 2025MallowsPO: Fine-Tune Your LLM with Preference Dispersions
202. ICLR 2025ManiSkill-HAB: A Benchmark for Low-Level Manipulation in Home Rearrangement Tasks
203. ICLR 2025MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
204. ICLR 2025MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
205. ICLR 2025Measuring And Improving Engagement of Text-to-Image Generation Models
206. ICLR 2025Measuring memorization in RLHF for code completion
207. ICLR 2025MetaUrban: An Embodied AI Simulation Platform for Urban Micromobility
208. ICLR 2025Minimax Optimal Reinforcement Learning with Quasi-Optimism
209. ICLR 2025Misspecified $Q$-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation Error
210. ICLR 2025Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
211. ICLR 2025Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
212. ICLR 2025Model Risk-sensitive Offline Reinforcement Learning
213. ICLR 2025Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
214. ICLR 2025Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
215. ICLR 2025Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds
216. ICLR 2025Model-Free Offline Reinforcement Learning with Enhanced Robustness
217. ICLR 2025Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
218. ICLR 2025Monte Carlo Planning with Large Language Model for Text-Based Game Agents
219. ICLR 2025Moral Alignment for LLM Agents
220. ICLR 2025More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
221. ICLR 2025Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
222. ICLR 2025Multi-agent cooperation through learning-aware policy gradients
223. ICLR 2025Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
224. ICLR 2025Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
225. ICLR 2025Neural Interactive Proofs
226. ICLR 2025Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion
227. ICLR 2025Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
228. ICLR 2025Neuroplastic Expansion in Deep Reinforcement Learning
229. ICLR 2025Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
230. ICLR 2025Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
231. ICLR 2025Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
232. ICLR 2025OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models
233. ICLR 2025ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
234. ICLR 2025Offline Hierarchical Reinforcement Learning via Inverse Optimization
235. ICLR 2025Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
236. ICLR 2025Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
237. ICLR 2025OGBench: Benchmarking Offline Goal-Conditioned RL
238. ICLR 2025OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code
239. ICLR 2025On a Connection Between Imitation Learning and RLHF
240. ICLR 2025On Generalization Across Environments In Multi-Objective Reinforcement Learning
241. ICLR 2025On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
242. ICLR 2025On Rollouts in Model-Based Reinforcement Learning
243. ICLR 2025On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback
244. ICLR 2025On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
245. ICLR 2025On the Modeling Capabilities of Large Language Models for Sequential Decision Making
246. ICLR 2025On-the-fly Preference Alignment via Principle-Guided Decoding
247. ICLR 2025Online Preference Alignment for Language Models via Count-based Exploration
248. ICLR 2025Online Reinforcement Learning in Non-Stationary Context-Driven Environments
249. ICLR 2025Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
250. ICLR 2025Online-to-Offline RL for Agent Alignment

FAQ

How many Reinforcement Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

6,885 in total: 1,070 in 2023, 1,190 in 2024, 1,640 in 2025, 2,985 in 2026.

How many Reinforcement Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 760 Reinforcement Learning papers, versus 784 the year before.

How many Reinforcement Learning papers are at ICLR 2026?

ICLR 2026 has 911 Reinforcement Learning papers, versus 379 the year before.

How many Reinforcement Learning papers are at ICML 2026?

ICML 2026 has 1,021 Reinforcement Learning papers, versus 405 the year before.

How many Reinforcement Learning papers are at CVPR 2026?

CVPR 2026 has 293 Reinforcement Learning papers, versus 72 the year before.

Which conference publishes the most Reinforcement Learning papers?

NeurIPS, with 2,494 papers from 2023 to 2026.